Identification of relevant drug targets is a vital step in the drug discovery and validation process. This is particularly important because many drugs have multiple intracellular targets, some of which are relevant for the activities of the drugs and others of which may be irrelevant and may in fact be responsible for the undesirable side effects of the drugs. Identification of relevant targets can often lead to the identification of more specific drugs with fewer side effects. In many cases, drug-target identification can be complicated and act as a bottleneck to drug marketing. One of the limiting steps in this process is the need to perform structure-activity relationship studies that can be time-, money-, and labor-intensive.
Current affinity-based target identification techniques are limited by the necessity to modify each drug individually (without losing bioactivity), while indirect, non-affinity based approaches are dependent on the drug's ability to induce specific biochemical or cellular readouts (Giaever et al. (1999) Nat Genet. 21: 278-283; Hughes et al. (2000) Cell 102: 109-126)
Affinity-based methods include matrix-based affinity detection and matrix-free affinity labeling. Matrix-based affinity detection fuses the small molecule of interest to a solid support or capturable moiety such as biotin. Such matrix-based methods typically require three basic conditions: 1) that the small molecule contains a derivatizable functionality, 2) that bioactivity/binding specificity of the small molecule is unaffected by the derivatization, and 3) that the matrix does not hinder the binding of target protein to drug. The latter two criteria cannot be predicted a priori. Matrix-free affinity labeling relies on the incorporation of radioisotope, photo-reactive or fluorescent labels into the small molecule of interest and must typically also satisfy criteria one and two above. In both affinity chromatography and matrix-free methods, proteins are incubated with the modified small molecule and the binding proteins are revealed by mass spectrometry following gel electrophoresis. Genetic and other versions of matrix-based affinity chromatography, e.g., yeast three-hybrid (Licitra and Liu (1996) Proc. Natl. Acad. Sci., USA, 93: 12817-12821) and phage display cloning (Sche et al. (1999) Chem Biol 6: 707-716), require tagged small molecules as well. Thus current affinity methods are limited to small molecules that contain derivatizable functionalities and whose bioactivity/binding is unaffected by the modification
Indirect, non-affinity based approaches, which infer drug targets/pathways from the physiological responses or biochemical signatures the drugs produce, have also been developed. For example, classical genetics relies on the isolation of drug-resistant mutations (Heitman et al. (1991) Science 253: 905-909) or gene dosage effects (Rine et al. (1983) Proc. Natl. Acad. Sci., USA, 80: 6750-6754), and several genome-wide methods also rely on fitness changes (Giaever et al. (1999) Nat Genet. 21: 278-283; Lum et al. (2004) Cell 116: 121-137; Parsons et al. (2004) Nat Biotechnol 22: 62-69; Luesch et al. (2005) Chem Biol 12: 55-63; Butcher et al. (2006) Nat Chem Biol 2: 103-109). An inherent limitation of these methods is that they are applicable only to drugs that affect cell growth/viability. Another powerful approach, genome-wide expression profiling (Hughes et al. (2000) Cell 102: 109-126; Lamb et al. (2006) Science 313: 1929-1935), on the other hand, is applicable only to drugs that induce major transcriptome changes. These genetic and large-scale “omic” profiling approaches are also primarily limited to yeast or other simple, well-characterized model organisms. Moreover, the “readout” is often far downstream from the drug target.